Cargando…
Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow
BACKGROUND: Worldwide, breast cancer is the main cause of cancer mortality in women. Most cases originate in mammary ductal cells that produce the nipple aspirate fluid (NAF). In cancer patients, this secretome contains proteins associated with the tumor microenvironment. NAF studies are challenging...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474050/ https://www.ncbi.nlm.nih.gov/pubmed/30999875 http://dx.doi.org/10.1186/s12885-019-5547-y |
_version_ | 1783412566912925696 |
---|---|
author | Brunoro, Giselle Villa Flor Carvalho, Paulo Costa Barbosa, Valmir C. Pagnoncelli, Dante De Moura Gallo, Claudia Vitória Perales, Jonas Zahedi, René Peiman Valente, Richard Hemmi Neves-Ferreira, Ana Gisele da Costa |
author_facet | Brunoro, Giselle Villa Flor Carvalho, Paulo Costa Barbosa, Valmir C. Pagnoncelli, Dante De Moura Gallo, Claudia Vitória Perales, Jonas Zahedi, René Peiman Valente, Richard Hemmi Neves-Ferreira, Ana Gisele da Costa |
author_sort | Brunoro, Giselle Villa Flor |
collection | PubMed |
description | BACKGROUND: Worldwide, breast cancer is the main cause of cancer mortality in women. Most cases originate in mammary ductal cells that produce the nipple aspirate fluid (NAF). In cancer patients, this secretome contains proteins associated with the tumor microenvironment. NAF studies are challenging because of inter-individual variability. We introduced a paired-proteomic shotgun strategy that relies on NAF analysis from both breasts of patients with unilateral breast cancer and extended PatternLab for Proteomics software to take advantage of this setup. METHODS: The software is based on a peptide-centric approach and uses the binomial distribution to attribute a probability for each peptide as being linked to the disease; these probabilities are propagated to a final protein p-value according to the Stouffer’s Z-score method. RESULTS: A total of 1227 proteins were identified and quantified, of which 87 were differentially abundant, being mainly involved in glycolysis (Warburg effect) and immune system activation (activated stroma). Additionally, in the estrogen receptor-positive subgroup, proteins related to the regulation of insulin-like growth factor transport and platelet degranulation displayed higher abundance, confirming the presence of a proliferative microenvironment. CONCLUSIONS: We debuted a differential bioinformatics workflow for the proteomic analysis of NAF, validating this secretome as a treasure-trove for studying a paired-organ cancer type. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-019-5547-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6474050 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-64740502019-04-24 Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow Brunoro, Giselle Villa Flor Carvalho, Paulo Costa Barbosa, Valmir C. Pagnoncelli, Dante De Moura Gallo, Claudia Vitória Perales, Jonas Zahedi, René Peiman Valente, Richard Hemmi Neves-Ferreira, Ana Gisele da Costa BMC Cancer Research Article BACKGROUND: Worldwide, breast cancer is the main cause of cancer mortality in women. Most cases originate in mammary ductal cells that produce the nipple aspirate fluid (NAF). In cancer patients, this secretome contains proteins associated with the tumor microenvironment. NAF studies are challenging because of inter-individual variability. We introduced a paired-proteomic shotgun strategy that relies on NAF analysis from both breasts of patients with unilateral breast cancer and extended PatternLab for Proteomics software to take advantage of this setup. METHODS: The software is based on a peptide-centric approach and uses the binomial distribution to attribute a probability for each peptide as being linked to the disease; these probabilities are propagated to a final protein p-value according to the Stouffer’s Z-score method. RESULTS: A total of 1227 proteins were identified and quantified, of which 87 were differentially abundant, being mainly involved in glycolysis (Warburg effect) and immune system activation (activated stroma). Additionally, in the estrogen receptor-positive subgroup, proteins related to the regulation of insulin-like growth factor transport and platelet degranulation displayed higher abundance, confirming the presence of a proliferative microenvironment. CONCLUSIONS: We debuted a differential bioinformatics workflow for the proteomic analysis of NAF, validating this secretome as a treasure-trove for studying a paired-organ cancer type. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12885-019-5547-y) contains supplementary material, which is available to authorized users. BioMed Central 2019-04-18 /pmc/articles/PMC6474050/ /pubmed/30999875 http://dx.doi.org/10.1186/s12885-019-5547-y Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Brunoro, Giselle Villa Flor Carvalho, Paulo Costa Barbosa, Valmir C. Pagnoncelli, Dante De Moura Gallo, Claudia Vitória Perales, Jonas Zahedi, René Peiman Valente, Richard Hemmi Neves-Ferreira, Ana Gisele da Costa Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow |
title | Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow |
title_full | Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow |
title_fullStr | Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow |
title_full_unstemmed | Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow |
title_short | Differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow |
title_sort | differential proteomic comparison of breast cancer secretome using a quantitative paired analysis workflow |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6474050/ https://www.ncbi.nlm.nih.gov/pubmed/30999875 http://dx.doi.org/10.1186/s12885-019-5547-y |
work_keys_str_mv | AT brunorogisellevillaflor differentialproteomiccomparisonofbreastcancersecretomeusingaquantitativepairedanalysisworkflow AT carvalhopaulocosta differentialproteomiccomparisonofbreastcancersecretomeusingaquantitativepairedanalysisworkflow AT barbosavalmirc differentialproteomiccomparisonofbreastcancersecretomeusingaquantitativepairedanalysisworkflow AT pagnoncellidante differentialproteomiccomparisonofbreastcancersecretomeusingaquantitativepairedanalysisworkflow AT demouragalloclaudiavitoria differentialproteomiccomparisonofbreastcancersecretomeusingaquantitativepairedanalysisworkflow AT peralesjonas differentialproteomiccomparisonofbreastcancersecretomeusingaquantitativepairedanalysisworkflow AT zahedirenepeiman differentialproteomiccomparisonofbreastcancersecretomeusingaquantitativepairedanalysisworkflow AT valenterichardhemmi differentialproteomiccomparisonofbreastcancersecretomeusingaquantitativepairedanalysisworkflow AT nevesferreiraanagiseledacosta differentialproteomiccomparisonofbreastcancersecretomeusingaquantitativepairedanalysisworkflow |